A systematic review and meta-analysis on the effects of physically active classrooms on educational and enjoyment outcomes in school age children
Bibliographic record
Abstract
OBJECTIVES: Despite the relationship between physical activity (PA) and learning outcomes, the school system has not been able to support the inclusion of PA throughout the day. A solution to this problem integrates PA into the academic classroom. The objective of this review is to determine the impact of active classrooms compared to traditional sedentary classrooms on educational outcomes of school-aged children. DESIGN: We searched ERIC, PubMed, PsychINFO, and Web of Science, reference lists of included studies for randomised controlled studies. Independent reviewers screened the texts of potentially eligible studies and assessed the risk of bias. Data were pooled using random-effects models on standardized mean differences. RESULTS: This review identified 25 studies examining educational outcomes, including approximately 6,181 students. Risk of bias was assessed as either some or high risk of bias for most of the studies and outcomes. Pooled data from 20 studies and 842 participants measuring academic performance shows a small positive effect of active classrooms compared with traditional, sedentary classrooms (SMD = 0.28, 95% CI: 0.09 to 0.47). CONCLUSIONS: Physically active classrooms may slightly improve academic achievement compared to the traditional sedentary lessons. Future research is needed to ensure that studies are adequately powered, employ appropriate methods of randomization, and measure a wide range of important student outcomes across the full spectrum of the school-age.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.011 | 0.036 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.017 | 0.020 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".